Purpose

This study statistically examines the shifting distribution channels in the American wine industry based on the growth trajectory of sales, seasonality and disruption due to consumers switching to online platforms. The purpose of this paper is to design a model that will have general applicability beyond the wine industry.

Design/methodology/approach

The research uses regression-based additive decomposition of time series data to predict the trajectory of the market share for the digital distribution channel. The study develops a statistical prediction model using time series data between 2007 and 2020, inclusive, sourced from US Annual Wine Reports and Bureau of Alcohol, Tobacco and Firearms databases.

Findings

The results show an increasing trajectory of wine sales through the online distribution channel with predictable seasonality. The disruptive effects of consumer switching behavior point to a steady increase in sales due both to increasing demand and accelerating switching. Nevertheless, the model shows that bricks and mortar purchases will remain strong and continue to account for the bulk of wine sales. COVID-19 has caused a step function increase in online sales but this should moderate after the crisis subsides and can be tested further.

Originality/value

This study is original in developing a model for an industry where bricks and mortar sales are growing and are expected to remain strong while there is still identifiable switching to online sales. The wine industry presents a classic case of accelerating switching behavior where there is still a strong franchise for in-store purchases. The model should have general applicability to distribution channels beyond the wine industry where steady growth, marked seasonality and disruptive consumer switching are in evidence.

中文翻译：

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美国葡萄酒在线季节性需求的时间序列预测模型以及 COVID-19 导致的供应渠道潜在中断

目的

本研究根据消费者转向在线平台导致的销售增长轨迹、季节性和中断，对美国葡萄酒行业的分销渠道变化进行了统计调查。本文的目的是设计一个模型，该模型将在葡萄酒行业之外具有普遍适用性。

设计/方法/方法

该研究使用基于回归的时间序列数据的加性分解来预测数字分销渠道的市场份额轨迹。该研究使用 2007 年至 2020 年（包括在内）的时间序列数据开发了一个统计预测模型，这些数据来自美国年度葡萄酒报告和酒精、烟草和枪支局数据库。

发现

结果显示，通过具有可预测季节性的在线分销渠道，葡萄酒销售的增长轨迹。消费者转换行为的破坏性影响表明，由于需求增加和转换加速，销售额稳步增长。尽管如此，该模型显示，实体店购买仍将保持强劲，并继续占葡萄酒销售的大部分。COVID-19 导致在线销售出现阶跃函数增长，但在危机消退后应该会有所缓和，并且可以进一步测试。

原创性/价值

这项研究最初是为一个实体销售正在增长的行业开发一个模型，并且预计在仍然可以识别到在线销售的情况下将保持强劲。葡萄酒行业呈现了一个加速转换行为的经典案例，其中仍然存在强大的店内购买特许经营权。该模型应该普遍适用于葡萄酒行业以外的分销渠道，在这些渠道中稳定增长、明显的季节性和颠覆性的消费者转换是显而易见的。